Optimizing a Seismic Survey for Source Separation

ABSTRACT

A technique includes determining at least one parameter that characterizes a seismic survey in which multiple interfering seismic sources are fired and seismic sensors sense energy that is produced by the seismic sources. The determination of the parameter(s) includes optimizing the seismic survey for separation of the sensed energy according to the seismic sources.

This application is a continuation of U.S. patent application Ser. No.12/174,310, “OPTIMIZING A SEISMIC SURVEY FOR SOURCE SEPARATION,” whichwas filed on Jul. 16, 2008, and is hereby incorporated by reference inits entirety.

BACKGROUND

The invention generally relates to optimizing a seismic survey forsource separation.

Seismic exploration involves surveying subterranean geologicalformations for hydrocarbon deposits. A survey typically involvesdeploying seismic source(s) and seismic sensors at predeterminedlocations. The sources generate seismic waves, which propagate into thegeological formations creating pressure changes and vibrations alongtheir way. Changes in elastic properties of the geological formationscatter the seismic waves, changing their direction of propagation andother properties. Part of the energy emitted by the sources reaches theseismic sensors. Some seismic sensors are sensitive to pressure changes(hydrophones), others to particle motion (e.g., geophones), andindustrial surveys may deploy only one type of sensors or both. Inresponse to the detected seismic events, the sensors generate electricalsignals to produce seismic data. Analysis of the seismic data can thenindicate the presence or absence of probable locations of hydrocarbondeposits.

Some surveys are known as “marine” surveys because they are conducted inmarine environments. However, “marine” surveys may be conducted not onlyin saltwater environments, but also in fresh and brackish waters. In onetype of marine survey, called a “towed-array” survey, an array ofseismic sensor-containing streamers and sources is towed behind a surveyvessel.

SUMMARY

In an embodiment of the invention, a technique includes determining atleast one parameter that characterizes a seismic survey in whichmultiple interfering seismic sources are fired and seismic sensors senseenergy that is produced by the seismic sources. The determination of theparameter(s) includes optimizing the seismic survey for separation ofthe sensed energy according to the seismic sources.

In an embodiment of the invention, a system includes seismic sources andseismic sensors, which are adapted to sense energy that is produced bythe firing of the seismic sources. The system is optimized forseparation of the sensed energy according to the seismic sources.

In yet another embodiment of the invention, a system includes a memoryand a processor. The memory stores instructions that when executed bythe processor cause the processor to process at least one parameter thatcharacterizes a seismic survey to optimize the seismic survey forseparation of sensed energy produced by multiple interfering seismicsources.

Advantages and other features of the invention will become apparent fromthe following drawing, description and claims.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a schematic diagram of a marine-based seismic acquisitionsystem according to an embodiment of the invention.

FIGS. 2, 3 and 4 are flow diagrams depicting techniques to design aseismic survey according to embodiments of the invention.

FIG. 5 is a schematic diagram of a data processing system according toan embodiment of the invention.

DETAILED DESCRIPTION

FIG. 1 depicts an embodiment 10 of a marine-based seismic dataacquisition system in accordance with some embodiments of the invention.In the system 10, a survey vessel 20 tows one or more seismic streamers30 (one exemplary streamer 30 being depicted in FIG. 1) behind thevessel 20. It is noted that the streamers 30 may be arranged in a spreadin which multiple streamers 30 are towed in approximately the same planeat the same depth. As another non-limiting example, the streamers may betowed at multiple depths, such as in an over/under spread, for example.

The seismic streamers 30 may be several thousand meters long and maycontain various support cables (not shown), as well as wiring and/orcircuitry (not shown) that may be used to support communication alongthe streamers 30. In general, each streamer 30 includes a primary cableinto which is mounted seismic sensors that record seismic signals. Thestreamers 30 contain seismic sensors 58, which may be, depending on theparticular embodiment of the invention, hydrophones (as one non-limitingexample) to acquire pressure data or multi-component sensors. Forembodiments of the invention in which the sensors 58 are multi-componentsensors (as another non-limiting example), each sensor is capable ofdetecting a pressure wavefield and at least one component of a particlemotion that is associated with acoustic signals that are proximate tothe sensor. Examples of particle motions include one or more componentsof a particle displacement, one or more components (inline (x),crossline (y) and vertical (z) components (see axes 59, for example)) ofa particle velocity and one or more components of a particleacceleration.

Depending on the particular embodiment of the invention, themulti-component seismic sensor may include one or more hydrophones,geophones, particle displacement sensors, particle velocity sensors,accelerometers, pressure gradient sensors, or combinations thereof.

For example, in accordance with some embodiments of the invention, aparticular multi-component seismic sensor may include a hydrophone formeasuring pressure and three orthogonally-aligned accelerometers tomeasure three corresponding orthogonal components of particle velocityand/or acceleration near the sensor. It is noted that themulti-component seismic sensor may be implemented as a single device (asdepicted in FIG. 1) or may be implemented as a plurality of devices,depending on the particular embodiment of the invention. A particularmulti-component seismic sensor may also include pressure gradientsensors, which constitute another type of particle motion sensors. Eachpressure gradient sensor measures the change in the pressure wavefieldat a particular point with respect to a particular direction. Forexample, one of the pressure gradient sensors may acquire seismic dataindicative of, at a particular point, the partial derivative of thepressure wavefield with respect to the crossline direction, and anotherone of the pressure gradient sensors may acquire, a particular point,seismic data indicative of the pressure data with respect to the inlinedirection.

The marine seismic data acquisition system 10 includes seismic sources40 (two exemplary seismic sources 40 being depicted in FIG. 1), such asair guns and the like. In some embodiments of the invention, the seismicsources 40 may be coupled to, or towed by, the survey vessel 20.Alternatively, in other embodiments of the invention, the seismicsources 40 may operate independently of the survey vessel 20, in thatthe sources 40 may be coupled to other vessels or buoys, as just a fewexamples.

As the seismic streamers 30 are towed behind the survey vessel 20,acoustic signals 42 (an exemplary acoustic signal 42 being depicted inFIG. 1), often referred to as “shots,” are produced by the seismicsources 40 and are directed down through a water column 44 into strata62 and 68 beneath a water bottom surface 24. The acoustic signals 42 arereflected from the various subterranean geological formations, such asan exemplary formation 65 that is depicted in FIG. 1.

The incident acoustic signals 42 that are created by the sources 40produce corresponding reflected acoustic signals, or pressure waves 60,which are sensed by the seismic sensors 58. It is noted that thepressure waves that are received and sensed by the seismic sensors 58include “up going” pressure waves that propagate to the sensors 58without reflection, as well as “down going” pressure waves that areproduced by reflections of the pressure waves 60 from an air-waterboundary 31.

The seismic sensors 58 generate signals (digital signals, for example),called “traces,” which indicate the acquired measurements of thepressure wavefield and particle motion. The traces are recorded and maybe at least partially processed by a signal processing unit 23 that isdeployed on the survey vessel 20, in accordance with some embodiments ofthe invention. For example, a particular seismic sensor 58 may provide atrace, which corresponds to a measure of a pressure wavefield by itshydrophone; and the sensor 58 may provide (depending on the particularembodiment of the invention) one or more traces that correspond to oneor more components of particle motion.

The goal of the seismic acquisition is to build up an image of a surveyarea for purposes of identifying subterranean geological formations,such as the exemplary geological formation 65. Subsequent analysis ofthe representation may reveal probable locations of hydrocarbon depositsin subterranean geological formations. Depending on the particularembodiment of the invention, portions of the analysis of therepresentation may be performed on the seismic survey vessel 20, such asby the signal processing unit 23. In accordance with other embodimentsof the invention, the representation may be processed by a seismic dataprocessing system that may be, for example, located on land or on thevessel 20. Thus, many variations are possible and are within the scopeof the appended claims.

A particular seismic source 40 may be formed from an array of seismicsource elements (such as air guns, for example) that may be arranged instrings (gun strings, for example) of the array. Alternatively, aparticular seismic source 40 may be formed from one or a predeterminednumber of air guns of an array, may be formed from multiple arrays, etc.Regardless of the particular composition of the seismic sources, thesources may be fired in a particular time sequence during the survey.

There are many physical constraints in acquiring seismic data, such asthe relationship of the record length to the acquisition efficiency.More specifically, the energy that is sensed by the seismic sensors dueto a given firing, or “shot,” of a seismic source typically is recordedfrom a time interval that spans from the time at which the shot occurredand ends slightly before the time at which the next shot occurs. Forpurposes of increasing the efficiency, techniques, such as the onedisclosed in U.S. Pat. No. 5,924,049, entitled “METHODS FOR ACQUIRINGAND PROCESSING SEISMIC DATA,” which issued on Jul. 13, 1999, allowmultiple seismic sources to fire simultaneously and essentially allowmore than one record to be recorded at the same time.

Therefore, the seismic sources 40 may be fired in a sequence such thatmultiple seismic sources 40 may be fired simultaneously or nearsimultaneously in a short interval of time so that a composite energysignal that is sensed by the seismic sensors 58 contains a significantamount of energy from more than one seismic source 40. In other words,the seismic sources interfere with each other such that the compositeenergy signal is not easily separable into signals that are attributedto the specific seismic sources. However, source separation techniquesmay be applied to process the acquired seismic data to form datasetsthat are each associated with one of the seismic sources 40 so that eachdataset ideally indicates the component of the composite seismic energysignal that is attributable to an associated seismic source 40. Thesource separation typically is not perfect such that some of the sensedenergy (called the “residual energy”) is ultimately not attributed toany of the seismic sources, and some of the sensed energy (called the“leakage energy”) may be attributed to the wrong seismic source by theseparation process.

The seismic survey has a number of characterizing parameters, whichaffect the quality of the source separation. More specifically, suchparameters as the timing sequence that governs the seismic sourcefirings, the source geometry (crossline and inline separations of airguns, for example) and the receiver geometry (the type of spread and thecrossline and inline separations of the seismic sensors 58, as examples)may influence how effectively the source energy is separated. Inaccordance with embodiments of the invention described herein, atechnique 150 that is depicted in FIG. 2 is used for purposes ofdesigning a seismic survey. Referring to FIG. 2, pursuant to thetechnique 150, a seismic survey is designed (block 154) in whichmultiple interfering seismic sources are fired. The acquired seismicdata are processed for purposes of separating the sensed source energyaccording to the seismic sources. Pursuant to block 158 of the technique150, the seismic survey is optimized for the separation of the sourceenergy. In other words, the technique 150 includes determining one ormore parameters of the survey for the purpose of optimizing sourceseparation.

As further described herein, the optimized survey parameters may beparameters related to the geometry of the seismic sources, such as thenumber of seismic sources, crossline source spacing, inline sourcespacing, specific source locations, etc.; the receiver geometry; thetimes at which the seismic sources are fired relative to each other(i.e., the timing sequence for the source firings); the relationshipbetween the timing sequence of source firings and frequency; etc.

Although a towed marine seismic survey is described herein for purposesof example, it is understood that the techniques and systems that aredescribed herein may be likewise be applied to any other type of surveythat has interfering seismic sources, such as non-towed marine surveys,land-based surveys, seabed cable-based surveys, vibroseis surveys, etc.For example, in accordance with other embodiments of the invention, suchparameters as source frequencies, source amplitudes and the sourcefiring timing sequence of a vibroseis survey may be optimized forpurposes of source separation.

As another example, in accordance with embodiments of the invention, thesystems and techniques that are described herein may be applied forpurposes of optimizing a borehole survey system in which the seismicsources and/or seismic sensors may be disposed in a wellbore. Thus, manyvariations are contemplated and are within the scope of the appendedclaims.

FIG. 3 depicts a system 200 for designing a seismic survey according tosome embodiments of the invention. The system 200 may be implementedsolely by software executing on one or more processor-based systems, ormay be implemented as a combination of software and hardware, dependingon the particular embodiment of the invention. The system 200 may beused when the survey geology is known (such as the geology that is knownfrom the results of a prior survey, for example) or at least when areasonable estimate of the survey geology may be determined. Forexample, the system 200 may be used, in accordance with some embodimentsof the invention, based on a 1D estimate, which assumes that the geologyonly varies in the vertical direction and does not vary in thehorizontal direction.

The system 200 includes a computer-based simulator 220 that applies anumerical processing technique for purposes of optimizing surveyparameters for source separation. More specifically, in accordance withsome embodiments of the invention, the computer-based simulator 220performs a Monte Carlo simulation, which models the survey system basedon randomly or pseudo randomly generated inputs. The simulation andinputs may be, however, subject to various constraints. Therefore,survey parameters, such as firing times, source geometry, receivergeometry (i.e., the geometry of the seismic sensors), etc., may berandomly or pseudo randomly varied within predefined ranges for purposesof determining the optimal survey parameters for source separation.

More specifically, as depicted for purposes of example in FIG. 3, thecomputer-based simulator 220 may receive data 216, which are indicativeof the survey geology, as well as data 214, 215 and 218, which areindicative of the source geometry, receiver geometry and firing times,respectively. It is noted that, depending on the particular embodimentof the invention, the source geometry data 214, receiver geometry data215 and firing time data 218 may be generated by random, pseudo randomor non-random source geometry 206, receiver geometry 205 and sourcefiring time 204 generators, respectively. Thus, the generators 204, 205and 206 may generate random source geometries, receiver geometries andfiring times within predefined ranges, in accordance with someembodiments of the invention.

The manner in which the source geometries, receiver geometries andfiring times are generated may be varied, depending on the particularembodiment of the invention. As examples, the source and receivergeometries may be held constant while the optimal firing times aredetermined; the source geometries, receiver geometries and firing timesmay simultaneously randomly varied; the firing times and receivergeometries may be held constant while optimal source geometry parametersare determined; etc. Thus, many variations are contemplated and arewithin the scope of the appended claims.

The computer-based simulator 220 generates a synthetic dataset 224,which is the seismic dataset that is predicted to be acquired by seismicsensors in an actual survey that is defined by the current surveygeology and survey parameters that are received as inputs by thecomputer-based simulator 220. The synthetic dataset 224 indicates thepredicted sensed composite energy signal that is produced by theinterfering seismic sources 40. Based on the synthetic dataset 224, asource energy separator 230 of the system 200 produces multipledatasets, each of which is attributable to a particular seismic source.

It is noted that the source energy separator 230 may employ a numericalinversion algorithm (performed via instructions executing on acomputer), which involves inversion of a linear system (as anon-limiting example). The source energy separation may be unable toattribute all of the energy to one of the seismic sources, which meansthe processing by the source energy separator 230 produces a residualenergy. Also, there is leakage energy, which is energy that is producedby one seismic source but is attributed to a different seismic source bythe separation process. Mathematically, if the recorded data ared=d₁+d₂, and the estimated data are d₁′ and d₂′, then the residual isd₁′+d₂′−d; and the leakage is d₁′−d₁ for seismic source S₁, and d₂′−d₂for seismic source S₂.

Thus, the residual and leakage energies indicate a degree of error inthe source separation, as ideally, the residual and leakage energies arezero, in that ideally all of the sensed energy is partitioned among andcorrectly to the seismic sources. Therefore, in accordance with someembodiments of the invention, optimization of the seismic survey occurswhen the seismic survey is characterized by a set of parameters thatminimizes the residual and leakage energies or at least producesresidual and leakage energies that are below selected thresholds.

In accordance with embodiments of the invention, a controller 240 of thesystem 200 receives data 234 from the source energy separator 230, whichis indicative of the residual energy. The controller 240 changes one ormore survey parameters (by changing the source firing times or sourcegeometry, as non-limiting examples), until, based on the residual energydata 234 and leakage energy data 235, the controller 240 determines thatthese energies have been sufficiently minimized. For example, thecontroller 240 may continue running the receiver geometry 205, sourcegeometry 206 and firing time 204 generators, the controller 240 maychange the input ranges, the controller 240 may hold some inputsconstant while varying others, etc. Once the controller 240 determinesthat the residual and leakage energies have been sufficiently minimized,the controller 240 provides data 244, which are indicative of theoptimal survey parameters.

In some cases, the survey geology may be unknown or a reliable estimateof the geology may be unavailable. For such cases, survey parameters maybe optimized for source energy separation based on a linear system thatcharacterizes the survey system. As a more specific example, referringto FIG. 4, in accordance with some embodiments of the invention, atechnique 250 to optimize survey parameters includes modeling (block254) seismic datasets as being determinable from a linear system that ischaracterized by a survey geology and survey parameters. Each dataset isassociated with the sensed energy uniquely attributable to a differentseismic source. The linear system may be inverted for the seismicdatasets. The survey parameters are optimized for source separation bymaximizing the accuracy of the inversion for the recovery of thedatasets, pursuant to block 258.

As a more specific example, in accordance with some embodiments of theinvention, source dithering (i.e., using a source firing timing sequencein which the source firing times are slightly offset for each other) maybe used for purposes of enabling the separation of interfering seismicsources as described in U.S. patent application Ser. No. 11/964,402,entitled, “SEPARATING SEISMIC SIGNALS PRODUCED BY INTERFERING SEISMICSOURCES,” (Attorney Docket No. 57.0820) which was filed on Dec. 26,2007. Linear operator transforms may be used in a model of the surveysystem for purposes of decomposing the sensed composite energy signalinto signals that are each uniquely associated with a particular seismicsource. The invertability of a matrix of this system is maximized forpurposes of determining an optimum survey design from the standpoint ofsource separation.

More specifically, the seismic data (referred to herein as a “seismicdata vector d”) is deemed to be acquired by seismic sensors due to thefirings of N (i.e., multiple) seismic sources. Thus, the simultaneous ornear simultaneous firing of the seismic sources causes significantenergy from all of these firings to be present in the seismic datavector d. Models, which describe the geology that affects the sourceenergy are associated with linear operators that describe the physics ofthe source mechanisms, the wave propagation and the survey geometry. Theseismic data vector d may then be characterized as a function of themodels and the linear operators. Thus, in theory, the function may bejointly inverted for the models, which permits the seismic data vector dto be separated into N seismic datasets d₁, d₂, d₃ . . . d_(N) such thateach dataset is uniquely attributable to one of the seismic sources. Inother words, each dataset represents a component of the sensed compositeenergy signal, which is uniquely attributable to one of the seismicsources.

As a more specific example, assume that the seismic data vector d isacquired due to the near simultaneous firing of two seismic sourcescalled “S₁” and “S₂.” For this example, the seismic sources S₁ and S₂are fired pursuant to a timing sequence, which may be based on apredetermined timing pattern or may be based on random or pseudo-randomtimes. Regardless of the particular timing scheme, it is assumed forthis example that the seismic source S₁ is fired before the seismicsource S₂ for all traces, and it is further assumed that the zero timesof the traces correspond to the firing times for S₁. Thus, the zerotimes of the traces are in “S₁ time.” The offsets, or vectors, to theseismic sources S₁ and S₂ are called “x¹” and “x²,” respectively. Thetiming delays, denoted by “t” for the seismic source S₂ are known foreach trace.

It is assumed for this example that the collection of traces are suchthat the values of t are random. In practice, this is the case for aCMP, receiver or common offset gather. For purposes of simplifying thisdiscussion, it is assumed that the trace in each gather may be locatedwith respect to the seismic source S₁ and seismic source S₂ using scalarquantities called “x¹ _(i),” and “x² _(i),” respectively. In thisnotation, the subscript “i” denotes the trace number in the gather. As amore specific example, for a CMP gather, “x¹ _(i)” may be the scalaroffset to the seismic source S₁, and these quantities are referred to asoffsets below. Similarly, “t_(i)” denotes the timing delay for thei^(th) trace.

The recorded energy for the seismic source S₁ may be modeled by applyinga linear operator called “L₁” (which represents the physics of theseismic source S₁, the wave propagation associated with the source S₁and the survey geometry associated with the seismic source S₁) to anunknown model called “m₁,” which describes the geology that affects theenergy that propagates from the seismic source S₁. The model m₁ containsone element for each parameter in the model space. Typically the modelspace may be parameterized by slowness or its square, corresponding tolinear or hyperbolic/parabolic Radon transforms, respectively. Thelinear operator L₁ is a function of the offsets to the source S₁, theparameters that characterize the model space, and time or frequency. Aseismic data vector d₁ contains one element for each trace (at each timeor frequency) and is the component of the seismic data d, which isassociated with the seismic source S₁. In other words, the seismic datavector d₁ represents the dataset attributable to the seismic source S₁.The seismic data vector d₁ may be described as follows:

d₁=L₁m₁  Eq. 1

The energy that is associated with the seismic source S₂ appearsincoherent in the seismic data vector d. However, the energy is relatedto a coherent dataset in which the firing times for the seismic sourceS₂ are at time zero (i.e., seismic source S₂ time) by the application oftime shifts t_(i) to the traces. A diagonal linear operator called “D₂”may be used for purposes of describing these time shifts, such that thecomponent of the seismic data vector d, which is associated with theseismic source S₂ and which is called “d₂” may be described as follows:

d₂=D₂L₂m₂  Eq. 2

In Eq. 2, a linear operator called “L₂” represents the physics of theseismic source S₂, the wave propagation associated with the seismicsource S₂ and the survey geometry associated with the seismic source S₂.Also in Eq. 2, a model called “m₂” describes the geology that affectsthe energy that propagates from the seismic source S₂.

The composite seismic energy signal that is recorded by the seismicsensors is attributable to both seismic sources S₁ and S₂. Thus, theseismic data vector d (i.e., the recorded data) is a combination of theseismic data vectors d₁ and d₂, as described below:

d=d ₁ +d ₂  Eq. 3

Due to the relationships in Eqs. 1, 2 and 3, the seismic data vector dmay be represented as the following linear system:

$\begin{matrix}{d = {{\begin{bmatrix}L_{1} & {D_{2}L_{2}}\end{bmatrix}\begin{bmatrix}m_{1} \\m_{2}\end{bmatrix}}.}} & {{Eq}.\mspace{14mu} 4}\end{matrix}$

Thus, Eq. 4 may be solved (i.e., jointly inverted) for the model vectorm (i.e., (m₁; m₂)) using standard techniques, such as the least squaresalgorithm; and after the model vector m is known, Eqs. 1 and 2 may beapplied with the models m₁ and m₂ for purposes of separating the seismicdata vector d into the seismic data vectors d₁ and d₂, i.e., into thedatasets that indicate the measurements attributable to each seismicsource.

Eq. 4 may be inverted in the frequency (ω) domain. In that case,(D₂)_(jk)=exp(−iωt_(j))δ_(jk) and (L_(s))_(jk)=exp(−iωt^(s) _(jk)),where t^(s) _(jk) is the time shift associated with offset x^(s) _(j)and the parameter for the k^(th) trace in the model space associatedwith S_(s). For a linear Radon transform parameterized by slowness,ρ^(s) _(k), t^(s) _(jk)=x^(s) _(j)ρ^(s) _(k). For a parabolic Radontransform parameterized by curvature, q^(s) _(k), t^(s) _(jk)=(x^(s)_(j))²q^(s) _(k).

The success of the source separation technique described above dependson the ability of the transform to separate the energy associated withthe two sources. Unlike most applications of Radon transforms, successdoes not depend on the ability to focus energy at the correct modelparameter within m₁ or m₂. When random or pseudo time delays are usedbetween source firings, the basis functions for the two model domains(t¹ _(jk) and t_(j)+t² _(jk)) are very different, and this enablesextremely effective separation of the sources.

In accordance with embodiments of the invention, survey parameters aredetermined that maximize the invertability of the matrix L=[L₁ D₂L₂](see Eq. 4) for purposes of optimizing the survey for source separation.It is noted that, as can be appreciated by one of skill in the art, thedegree of invertability of a matrix may be evaluated by such techniquesas evaluating the Hessian, the condition number of the matrix, thesparseness of the matrix and the matrix's eigenvalue distribution. Thus,the optimal survey parameters (timing sequence of source firings, sourcegeometry, etc.) are the parameters that maximize the matrix'sinvertability.

It is noted that making L invertible is sufficient for optimization butnot required. If L is invertible, then d=Lm may be solved for m, where

${m = \begin{pmatrix}m_{1} \\m_{2}\end{pmatrix}},$

but m₁ and m₂ do not need to be recovered explicitly. It is enough torecover d₁ and d₂, as given by Eq. 1 and 2. The “wrong” m₁ and m₂, maybe recovered, but the correct d₁ and d₂ are recovered. This happensprovided m₁ models all the energy associated with the seismic source S₁and m₂ models all of the energy associated with the seismic source S₂,etc., even though it is in the wrong place within the model. It ismaximizing the invertibility of L in this generalised sense that isimportant.

Mathematically, if M is defined as

$\begin{pmatrix}M_{1} \\M_{2}\end{pmatrix},$

a generalized inverse of L, then the estimate of

$\quad\begin{pmatrix}d_{1} \\d_{2}\end{pmatrix}$

is as follows:

$\begin{matrix}{{\begin{pmatrix}L_{1} & 0 \\0 & {D_{2}L_{2}}\end{pmatrix}\begin{pmatrix}M_{1} \\M_{2}\end{pmatrix}( {{L_{1}m_{1}} + {D_{2}L_{2}m_{2}}} )},} & {{Eq}.\mspace{14mu} 5}\end{matrix}$

The data d₁ is considered to be of the form L₁m₁ etc., so M₁ and M₂satisfy the following relationship:

$\begin{matrix}{{\begin{pmatrix}{L_{1}m_{1}} \\{D_{2}L_{2}m_{2}}\end{pmatrix} = {\begin{pmatrix}{L_{1}M_{1}L_{1}} & {L_{1}M_{1}D_{2}L_{2}} \\{D_{2}L_{2}M_{2}L_{1}} & {D_{2}L_{2}M_{2}D_{2}L_{2}}\end{pmatrix}\begin{pmatrix}m_{1} \\m_{2}\end{pmatrix}}},} & {{Eq}.\mspace{14mu} 6} \\{or} & \; \\{{\begin{pmatrix}{L_{1}( {{M_{1}L_{1}} - I} )} & {L_{1}M_{1}D_{2}L_{2}} \\{D_{2}L_{2}M_{2}L_{1}} & {D_{2}{L_{2}( {{M_{2}D_{2}L_{2}} - I} )}}\end{pmatrix}\begin{pmatrix}m_{1} \\m_{2}\end{pmatrix}} = 0.} & {{Eq}.\mspace{14mu} 7}\end{matrix}$

Eq. 7 is satisfied for all m₁ and m₂, so L₁(M₁L₁−I)=0, L₁M₁D₂L₂=0,D₂L₂M₂L₁=0 and D₂L₂ (M₂D₂L₂−I)=0, where “I” represents the identitymatrix. This is more general, and more easily satisfied than making Mthe inverse of L, which requires M₁L₁=1, M₁D₂L₂=0, M₂L₁=0 and M₂D₂L₂=I.For example, M₁D₂L₂ needs to be in the null space of L₁ and notnecessarily zero.

Although by way of example a linear system has been described herein, itis noted that the survey may be optimized for source separation using anon-linear system, in accordance with other embodiments of theinvention.

Referring to FIG. 5, in accordance with some embodiments of theinvention, a data processing system 320 may perform at least some partsof one or more of the techniques that are disclosed herein for purposesof optimizing a seismic survey for source separation. In accordance withsome embodiments of the invention, the system 320 may include aprocessor 350, such as one or more microprocessors and/ormicrocontrollers. The processor 350 may be located on a streamer 30(FIG. 1), located on the vessel 20 or located at a land-based processingfacility (as examples), depending on the particular embodiment of theinvention.

The processor 350 may be coupled to a communication interface 360 forpurposes of receiving such data as acquired seismic data, geologymeasurement data, geology estimate data, survey parameter dataindicative of constraints for the survey parameters, ranges for thesurvey parameters, etc. In accordance with embodiments of the inventiondescribed herein, the processor 350, when executing instructions storedin a memory of the seismic data processing system 320, may implement oneor more of the processing blocks that are depicted in FIG. 3 or may aidin performing one or more of the processing steps depicted in FIGS. 2and 4.

As examples, the communication interface 360 may be a Universal SerialBus (USB) interface, a network interface, a removable media (such as aflash card, CD-ROM, etc.) interface or a magnetic storage interface (IDEor SCSI interfaces, as examples). Thus, the communication interface 360may take on numerous forms, depending on the particular embodiment ofthe invention.

In accordance with some embodiments of the invention, the communicationinterface 360 may be coupled to a memory 340 of the system 320 and maystore, for example, various input and/or output datasets involved in thedetermination of the optimal survey parameters. The memory 340 may storeprogram instructions 344, which when executed by the processor 350, maycause the processor 350 to perform various tasks of one or more of thetechniques and systems that are disclosed herein, such as the techniques150 or 250 and the system 200 and display results obtained via thetechnique(s)/system on a display (not shown in FIG. 5) of the system320, in accordance with some embodiments of the invention.

Other embodiments are within the scope of the appended claims. Forexample, although a towed marine-based seismic acquisition system hasbeen described above, the techniques and systems described herein foroptimizing a survey for source separation may likewise be applied toother types of seismic acquisition systems. As non-limiting examples,the techniques and system that are described herein may be applied toseabed, borehole and land-based seismic acquisition systems. Thus, theseismic sensors and sources may be stationary or may be towed, dependingon the particular embodiment of the invention.

As additional examples of other embodiments of the invention, techniquesother than those described above may be used to optimize a survey forsource separation. As examples, as can be appreciated by one of skill inthe art, such techniques as a Genetic Algorithm, Simulated AnnealingAlgorithm, Steepest Descent Algorithm or Conjugate Gradient Algorithmmay be used to determine optimal survey parameters, in other embodimentsof the invention.

While the present invention has been described with respect to a limitednumber of embodiments, those skilled in the art, having the benefit ofthis disclosure, will appreciate numerous modifications and variationstherefrom. It is intended that the appended claims cover all suchmodifications and variations as fall within the true spirit and scope ofthis present invention.

1. A method comprising: determining at least one characterizingparameter of a seismic survey in which multiple interfering seismicsources are fired and seismic sensors concurrently sense energy producedby the seismic sources to optimize the seismic survey for separation ofthe sensed energy according to the seismic sources, the optimizingcomprising: predicting a dataset to be acquired by the seismic sensorsbased on a geology associated with the survey; and determining said atleast one parameter based at least in part on a degree of separationindicated by the predicted dataset.
 2. The method of claim 1, whereinthe act of optimizing comprises optimizing a timing sequence thatgoverns the firing of seismic sources.
 3. The method of claim 1, whereinthe act of optimizing comprises optimizing a geometry of the seismicsources.
 4. The method of claim 3, wherein the act of optimizingcomprises optimizing an inline spacing or a crossline spacing of theseismic sources.
 5. The method of claim 1, wherein the act of optimizingcomprises optimizing a geometry of the seismic sensors.
 6. The method ofclaim 5, wherein the act of optimizing comprises optimizing an inlinespacing or a crossline spacing of the seismic sensors.
 7. The method ofclaim 1, wherein the seismic survey comprises a vibroseis survey.
 8. Themethod of claim 1, wherein the seismic survey comprises a marine survey.9. The method of claim 1, wherein the seismic survey comprises a towedsurvey.
 10. The method of claim 1, wherein the seismic survey comprisesa borehole survey.
 11. The method of claim 1, wherein the optimizingcomprises: determining a geology associated with the survey.
 12. Themethod of claim 11, wherein the determined geology comprises anestimated geology.
 13. The method of claim 11, wherein the determinedgeology comprises a geology determined from a survey.
 14. The method ofclaim 11, wherein the sensed energy is separated by inverting a linearsystem of equations for seismic datasets, each dataset beingattributable to one of the sources
 15. The method of claim 14, furthercomprising: determining at least one parameter to maximize accuracy ofthe inversion for the datasets.
 16. The method of claim 15, wherein theact of determining said at least one parameter comprises determining acondition number, a sparseness or an eigenvalue distribution of thematrix.
 17. The method of claim 1, wherein the act of optimizingcomprises modeling the seismic survey as a nonlinear system.
 18. Themethod of claim 1, wherein the sensed energy is separated by filteringto generate seismic datasets.
 19. The method of claim 1, wherein thesensed energy is separated by determining a residual energy not beingassociated with one of the seismic sources after separation of theenergy and a leakage energy associated with the wrong seismic source togenerate seismic datasets, each dataset being attributable to one of thesources.